Predictors of rapid eye movement sleep behavior disorder in patients with Parkinson's disease based on random forest and decision tree.

BACKGROUND AND OBJECTIVES: Sleep disorders related to Parkinson's disease (PD) have recently attracted increasing attention, but there are few clinical reports on the correlation of Parkinson's disease patients with rapid eye movement (REM) sleep behavior disorder (RBD). Therefore, this study conducted a cognitive function examination for Parkinson's disease patients and discussed the application effect of three algorithms in the screening of influencing factors and risk prediction effects. METHODS: Three algorithms (logistic regression, machine learning-based regression trees and random forest) were used to establish a prediction model for PD-RBD patients, and the application effects of the three algorithms in the screening of influencing factors and the risk prediction of PD-RBD were discussed. RESULTS: The subjects included 169 patients with Parkinson's disease (Parkinson's disease with RBD [PD-RBD] = 69 subjects; Parkinson's disease without RBD [PD-nRBD] = 100 subjects). This study compared the predictive performance of RF, decision tree and logistic regression, selected a final model with the best model performance and proposed the importance of variables in the final model. After the analysis, the accuracy of RF (83.05%) was better than that of the other models (decision tree = 75.10%, logistic regression = 71.62%). PQSI, Scopa-AUT score, MoCA score, MMSE score, AGE, LEDD, PD-course, UPDRS total score, ESS score, NMSQ, disease type, RLSRS, HAMD, UPDRS III and PDOnsetage are the main variables for predicting RBD, along with increased weight. Among them, PQSI is the most important factor. The prediction model of Parkinson's disease RBD that was established in this study will help in screening out predictive factors and in providing a reference for the prognosis and preventive treatment of PD-RBD patients. CONCLUSIONS: The random forest model had good performance in the prediction and evaluation of PD-RBD influencing factors and was superior to decision tree and traditional logistic regression models in many aspects, which can provide a reference for the prognosis and preventive treatment of PD-RBD patients.

Mediating effects of self-esteem on the relationship between mindful parenting and social anxiety level in Chinese adolescents.

This study aimed to investigate the relationship between mindful parenting and social anxiety level in Chinese adolescents and to explore the mediating roles of self-esteem between mindful parenting and social anxiety level. A total of 302 adolescents and their main caregivers were investigated by using the Chinese version of the Mindful Parenting Scale, Self-Esteem Scale and the Center for Epidemiological Studies Depression Scale and the Social Anxiety Scale. Related analysis was used to investigate the relationship between mindful parenting, self-esteem and social anxiety level. Mindful parenting and self-esteem were significantly associated with social anxiety level. Self-esteem mediated the relationship between mindful parenting and social anxiety level. Both mindful discipline and being in the moment influenced adolescents' social anxiety level through self-esteem. Self-esteem completely mediated the association between mindful parenting and social anxiety level. Longitudinal research is needed to better understand the relationship between mindful parenting and social anxiety level in adolescents.